Senior DevOps Engineer: Scalable Cloud Infra (GCP/K8s)

Nuuly; Philadelphia (Philadelphia County); On-site; USD 120,000 - 180,000; Full time

Job summary

Nuuly is seeking a DevOps Engineer to join the Platform Engineering team to scale production infrastructure on GCP and Kubernetes. You will design, implement, and maintain cloud services, CI/CD pipelines, and robust monitoring while guiding business teams in adopting scalable features.

You will optimize Kafka-based messaging, ensure security, and collaborate with cross-functional teams to improve performance and reliability across the stack.

Qualifications

• 3+ years in DevOps with cloud infrastructure focus.
• Experience with streaming data and asynchronous brokers (Kafka).
• Familiar with IaC tools like Terraform or Ansible.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.

Responsibilities

• Design, implement, and manage scalable cloud infrastructure on GCP.
• Collaborate with software teams to establish CI/CD pipelines.
• Implement monitoring, logging, and alerting for reliability and security.
• Optimize Kafka-based event streaming and brokers.
• Identify performance bottlenecks and tune the system.
• Ensure security best practices for cloud infrastructure.
• Troubleshoot deployment and infrastructure issues.
• Document infrastructure and deployment processes.
• Stay current with cloud trends and propose improvements.

Skills

Problem solving

Analytical thinking

Communication

Teamwork

Tools

Terraform

Ansible

Deployment Manager

Kubernetes

GitHub Actions

Zookeeper

Kafka

Job description

Nuuly is seeking a DevOps Engineer to join the Platform Engineering team to scale production infrastructure on GCP and Kubernetes. You will design, implement, and maintain cloud services, CI/CD pipelines, and robust monitoring while guiding business teams in adopting scalable features.

You will optimize Kafka-based messaging, ensure security, and collaborate with cross-functional teams to improve performance and reliability across the stack.